diff --git a/internal/face/detector.go b/internal/face/detector.go
index 660f0812c..049afa5df 100644
--- a/internal/face/detector.go
+++ b/internal/face/detector.go
@@ -140,11 +140,11 @@ func (fd *Detector) Detect(fileName string) (faces []pigo.Detection, params pigo
 	var maxSize int
 
 	if cols < 20 || rows < 20 || cols < fd.minSize || rows < fd.minSize {
-		return faces, params, fmt.Errorf("image too small (%dx%d)", cols, rows)
+		return faces, params, fmt.Errorf("image size %dx%d is too small", cols, rows)
 	} else if cols < rows {
-		maxSize = cols - 10
+		maxSize = cols - 8
 	} else {
-		maxSize = rows - 10
+		maxSize = rows - 8
 	}
 
 	imageParams := &pigo.ImageParams{
@@ -166,6 +166,8 @@ func (fd *Detector) Detect(fileName string) (faces []pigo.Detection, params pigo
 		ImageParams: *imageParams,
 	}
 
+	log.Debugf("faces: image size %dx%d, face size min %d, max %d", cols, rows, params.MinSize, params.MaxSize)
+
 	// Run the classifier over the obtained leaf nodes and return the Face results.
 	// The result contains quadruplets representing the row, column, scale and Face score.
 	faces = classifier.RunCascade(params, fd.angle)
diff --git a/internal/face/net.go b/internal/face/net.go
index 080f5662f..0aa82eb0f 100644
--- a/internal/face/net.go
+++ b/internal/face/net.go
@@ -150,7 +150,7 @@ func (t *Net) getFaceCrop(fileName, cacheHash string, f *Face) (img image.Image,
 	} else if img, err := imaging.Open(cacheFile); err != nil {
 		log.Errorf("faces: failed loading %s", filepath.Base(cacheFile))
 	} else {
-		log.Debugf("faces: using %s", filepath.Base(cacheFile))
+		log.Debugf("faces: extracting from %s", filepath.Base(cacheFile))
 		return img, nil
 	}